A Unified AI Framework for Network Intrusion Detection and Mobile Biometric Authentication in Indian Ecosystems

India’s rapid digital expansion has amplified both the opportunities and risks associated with digital identity and cybersecurity. Traditional rule-based approaches struggle to adapt to dynamic threats in real-time, while current AI implementations are often fragmented and imported from Western contexts, limiting their applicability in India’s diverse technological landscape. This paper introduces a dual-domain AI security framework that integrates CNN-based models for both network intrusion detection and facial biometric authentication. The system is trained and evaluated on a combination of global benchmarks and Indian-specific datasets, addressing challenges of adversarial robustness, demographic fairness, and explainability. The proposed architecture demonstrates high detection accuracy, resilience under attack, and equitable performance across population subgroups. It also aligns with India’s emerging data protection norms and mobile infrastructure limitations, providing a scalable solution suitable for deployment across public and private digital services.